I am fairly new using R and I am following a guide and learning to build an Expected Goals Model for my hockey league. When I run the code below, I get the error at the bottom. Is there something simple that I am missing?
Seems like its trying to use a formula in the model portion of the workflow but I already have a recipe in there. Thanks in advance for any help anyone can offer me! The guide is here https://www.thesignificantgame.com/portfolio/expected-goals-model-with-tidymodels/
library(tidymodels)
library(tidyverse)
library(dplyr)
set.seed(1972)
train_test_split <- initial_split(data = EXPECTED_GOALS_MODEL, prop = 0.80)
train_data <- train_test_split %>% training()
test_data <- train_test_split %>% testing()
xg_recipe <- recipe(Goal ~ DistanceC + Angle + Home + Hand + AgeDec31 + GoalieAgeDec31 + NewX + NewY, data = train_data) %>% update_role(NewX, NewY, new_role = "ID")
model <- logistic_reg() %>% set_engine("glm")
xg_wflow <- workflow() %>% add_model(model) %>% add_recipe(xg_recipe)
xg_wflow
xg_fit <- xg_wflow %>% fit(data = train_data)
Error in validObject(.Object) :
invalid class “model” object: invalid object for slot "formula" in class "model": got class "workflow", should be or extend class "formula"
In addition: Warning message:
In fit(., data = train_data) :
fit failed: Error in as.matrix(y) : argument "y" is missing, with no default
fit(x = ., data = train_data)
It's difficult to tell exactly what the issue is without a reproducible example, though this error brings up a few questions up for me:
EXPECTED_GOALS_MODEL data indeed have a column called Goal in it, with two unique levels? Have you also spelled the remainder of the column names correctly?generics::fit(data = train_data) instead of fit(data = train_data)? This almost looks like a different fit() is being dispatched to.Here's a place to start with a reprex:
library(tidymodels)
data(ames)
set.seed(1972)
ames <- ames %>% rowid_to_column()
train_test_split <- initial_split(data = ames, prop = 0.80)
train_data <- train_test_split %>% training()
test_data <- train_test_split %>% testing()
xg_recipe <- recipe(Sale_Price ~ ., data = train_data) %>% update_role(rowid, new_role = "ID")
model <- linear_reg() %>% set_engine("glm")
xg_wflow <- workflow() %>% add_model(model) %>% add_recipe(xg_recipe)
xg_fit <- xg_wflow %>% fit(data = train_data)
xg_fit
#> ══ Workflow [trained] ══════════════════════════════════════════════════════════
#> Preprocessor: Recipe
#> Model: linear_reg()
#>
#> ── Preprocessor ────────────────────────────────────────────────────────────────
#> 0 Recipe Steps
#>
#> ── Model ───────────────────────────────────────────────────────────────────────
#>
#> Call: stats::glm(formula = ..y ~ ., family = stats::gaussian, data = data)
#>
#> Coefficients:
#> (Intercept)
#> -2.583e+07
#> MS_SubClassOne_Story_1945_and_Older
#> 7.419e+03
#> MS_SubClassOne_Story_with_Finished_Attic_All_Ages
#> 1.562e+04
#> MS_SubClassOne_and_Half_Story_Unfinished_All_Ages
#> 1.060e+04
#> MS_SubClassOne_and_Half_Story_Finished_All_Ages
#> 8.413e+03
#> MS_SubClassTwo_Story_1946_and_Newer
#> 3.007e+03
#> MS_SubClassTwo_Story_1945_and_Older
#> 1.793e+04
#> MS_SubClassTwo_and_Half_Story_All_Ages
#> -3.909e+03
#> MS_SubClassSplit_or_Multilevel
#> -1.098e+04
#> MS_SubClassSplit_Foyer
#> -4.038e+03
#> MS_SubClassDuplex_All_Styles_and_Ages
#> -2.004e+04
#> MS_SubClassOne_Story_PUD_1946_and_Newer
#> -2.335e+04
#> MS_SubClassOne_and_Half_Story_PUD_All_Ages
#> -2.482e+04
#> MS_SubClassTwo_Story_PUD_1946_and_Newer
#> -1.794e+04
#> MS_SubClassPUD_Multilevel_Split_Level_Foyer
#> -2.098e+04
#> MS_SubClassTwo_Family_conversion_All_Styles_and_Ages
#> 6.903e+03
#> MS_ZoningResidential_High_Density
#> -3.853e+03
#> MS_ZoningResidential_Low_Density
#> -3.661e+03
#> MS_ZoningResidential_Medium_Density
#> -8.240e+03
#> MS_ZoningA_agr
#> -3.824e+03
#> MS_ZoningC_all
#> -1.800e+04
#> MS_ZoningI_all
#> -3.299e+04
#> Lot_Frontage
#> 1.336e+01
#>
#> ...
#> and 506 more lines.
Created on 2022-09-28 by the reprex package (v2.0.1)
Hope this helps!
Simon, tidymodels team